At the nexus of three kingdoms: the genome of the mycorrhizal fungus Gigaspora margarita provides insights into plant, endobacterial and fungal interactions.

As members of the plant microbiota, arbuscular mycorrhizal fungi (AMF, Glomeromycotina) symbiotically colonize plant roots. AMF also possess their own microbiota, hosting some uncultivable endobacteria. Ongoing research has revealed the genetics underlying plant responses to colonization by AMF, but the fungal side of the relationship remains in the dark. Here, we sequenced the genome of Gigaspora margarita, a member of the Gigasporaceae in an early diverging group of the Glomeromycotina. In contrast to other AMF, G. margarita may host distinct endobacterial populations and possesses the largest fungal genome so far annotated (773.104 Mbp), with more than 64% transposable elements. Other unique traits of the G. margarita genome include the expansion of genes for inorganic phosphate metabolism, the presence of genes for production of secondary metabolites and a considerable number of potential horizontal gene transfer events. The sequencing of G. margarita genome reveals the importance of its immune system, shedding light on the evolutionary pathways that allowed early diverging fungi to interact with both plants and bacteria

TRAPID : an efficient online tool for the functional and comparative analysis of de novo RNA-Seq transcriptomes

Transcriptome analysis through next-generation sequencing technologies allows the generation of detailed gene catalogs for non-model species, at the cost of new challenges with regards to computational requirements and bioinformatics expertise. Here, we present TRAPID, an online tool for the fast and efficient processing of assembled RNA-Seq transcriptome data, developed to mitigate these challenges. TRAPID offers high-throughput open reading frame detection, frameshift correction and includes a functional, comparative and phylogenetic toolbox, making use of 175 reference proteomes. Benchmarking and comparison against state-of-the-art transcript analysis tools reveals the efficiency and unique features of the TRAPID system

Genome of the pitcher plant <i>Cephalotus </i>reveals genetic changes associated with carnivory

Carnivorous plants exploit animals as a nutritional source and have inspired long-standing questions about the origin and evolution of carnivory-related traits. To investigate the molecular bases of carnivory, we sequenced the genome of the heterophyllous pitcher plant Cephalotus follicularis, in which we succeeded in regulating the developmental switch between carnivorous and non-carnivorous leaves. Transcriptome comparison of the two leaf types and gene repertoire analysis identified genetic changes associated with prey attraction, capture, digestion and nutrient absorption. Analysis of digestive fluid proteins from C. follicularis and three other carnivorous plants with independent carnivorous origins revealed repeated co-options of stress-responsive protein lineages coupled with convergent amino acid substitutions to acquire digestive physiology. These results imply constraints on the available routes to evolve plant carnivory

A high‐quality functional genome assembly of delia radicum L. (diptera: anthomyiidae) annotated from egg to adult

Abstract Belowground herbivores are overseen and underestimated, even though they can cause significant economic losses in agriculture. The cabbage root fly Delia radicum (Anthomyiidae) is a common pest in Brassica species, including agriculturally important crops, such as oilseed rape. The damage is caused by the larvae, which feed specifically on the taproots of Brassica plants until they pupate. The adults are aboveground‐living generalists feeding on pollen and nectar. Female flies are attracted by chemical cues in Brassica plants for oviposition. An assembled and annotated genome can elucidate which genetic mechanisms underlie the adaptation of D . radicum to its host plants and their specific chemical defences, in particular isothiocyanates. Therefore, we assembled, annotated and analysed the D . radicum genome using a combination of different next‐generation sequencing and bioinformatic approaches. We assembled a chromosome‐level D . radicum genome using PacBio and Hi‐C Illumina sequence data. Combining Canu and 3D‐DNA genome assembler, we constructed a 1.3 Gbp genome with an N50 of 242 Mbp and 6 pseudo‐chromosomes. To annotate the assembled D . radicum genome, we combined homology‐, transcriptome‐ and ab initio‐prediction approaches. In total, we annotated 13,618 genes that were predicted by at least two approaches. We analysed egg, larval, pupal and adult transcriptomes in relation to life‐stage specific molecular functions. This high‐quality annotated genome of D . radicum is a first step to understanding the genetic mechanisms underlying host plant adaptation. As such, it will be an important resource to find novel and sustainable approaches to reduce crop losses to these pests

Chromosome-level genome assembly of largemouth bass (Micropterus salmoides) using PacBio and Hi-C technologies

The largemouth bass (Micropterus salmoides) has become a cosmopolitan species due to its widespread introduction as game or domesticated fish. Here a high-quality chromosome-level reference genome of M. salmoides was produced by combining Illumina paired-end sequencing, PacBio single molecule sequencing technique (SMRT) and High-through chromosome conformation capture (Hi-C) technologies. Ultimately, the genome was assembled into 844.88 Mb with a contig N50 of 15.68 Mb and scaffold N50 length of 35.77 Mb. About 99.9% assembly genome sequences (844.00 Mb) could be anchored to 23 chromosomes, and 98.03% assembly genome sequences could be ordered and directed. The genome contained 38.19% repeat sequences and 2693 noncoding RNAs. A total of 26,370 protein-coding genes from 3415 gene families were predicted, of which 97.69% were functionally annotated. The high-quality genome assembly will be a fundamental resource to study and understand how M. salmoides adapt to novel and changing environments around the world, and also be expected to contribute to the genetic breeding and other research.info:eu-repo/semantics/publishedVersio

An approach to improved microbial eukaryotic genome annotation

Les nouvelles technologies de séquençage d’ADN ont accélérées la vitesse à laquelle les données génomiques sont générées. Par contre, une fois séquencées et assemblées, un défi continu est l'annotation structurelle précise de ces nouvelles séquences génomiques. Par le séquençage et l'assemblage du transcriptome (RNA-Seq) du même organisme, la précision de l'annotation génomique peut être améliorée, car les lectures de RNA-Seq et les transcrits assemblés fournissent des informations précises sur la structure des gènes. Plusieurs pipelines bio-informatiques actuelles incorporent des informations provenant du RNA-Seq ainsi que des données de similarité des séquences protéiques, pour automatiser l'annotation structurelle d’un génome de manière que la qualité se rapproche à celle de l'annotation par des experts. Les pipelines suivent généralement un flux de travail similaire. D'abord, les régions répétitives sont identifiées afin d'éviter de fausser les alignements de séquences et les prédictions de gènes. Deuxièmement, une base de données est construite contenant les données expérimentales telles que l’alignement des lectures de séquences, des transcrits et des protéines, ce qui informe les prédictions de gènes basées sur les Modèles de Markov Cachés généralisés. La dernière étape est de consolider les alignements de séquences et les prédictions de gènes dans un consensus de haute qualité. Or, les pipelines existants sont complexes et donc susceptibles aux biais et aux erreurs, ce qui peut empoisonner les prédictions de gènes et la construction de modèles consensus. Nous avons développé une approche améliorée pour l'annotation des génomes eucaryotes microbiens. Notre approche comprend deux aspects principaux. Le premier est axé sur la création d'un ensemble d'évidences extrinsèques le plus complet et diversifié afin de mieux informer les prédictions de gènes. Le deuxième porte sur la construction du consensus du modèle de gènes en utilisant les évidences extrinsèques et les prédictions par MMC, tel que l'influence de leurs biais potentiel soit réduite. La comparaison de notre nouvel outil avec trois pipelines populaires démontre des gains significatifs de sensibilité et de spécificité des modèles de gènes, de transcrits, d'exons et d'introns dans l’annotation structural de génomes d’eucaryotes microbiens.New sequencing technologies have considerably accelerated the rate at which genomic data is being generated. One ongoing challenge is the accurate structural annotation of those novel genomes once sequenced and assembled, in particular if the organism does not have close relatives with well-annotated genomes. Whole-transcriptome sequencing (RNA-Seq) and assembly—both of which share similarities to whole-genome sequencing and assembly, respectively—have been shown to dramatically increase the accuracy of gene annotation. Read coverage, inferred splice junctions and assembled transcripts can provide valuable information about gene structure. Several annotation pipelines have been developed to automate structural annotation by incorporating information from RNA-Seq, as well as protein sequence similarity data, with the goal of reaching the accuracy of an expert curator. Annotation pipelines follow a similar workflow. The first step is to identify repetitive regions to prevent misinformed sequence alignments and gene predictions. The next step is to construct a database of evidence from experimental data such as RNA-Seq mapping and assembly, and protein sequence alignments, which are used to inform the generalised Hidden Markov Models of gene prediction software. The final step is to consolidate sequence alignments and gene predictions into a high-confidence consensus set. Thus, automated pipelines are complex, and therefore susceptible to incomplete and erroneous use of information, which can poison gene predictions and consensus model building. Here, we present an improved approach to microbial eukaryotic genome annotation. Its conception was based on identifying and mitigating potential sources of error and bias that are present in available pipelines. Our approach has two main aspects. The first is to create a more complete and diverse set of extrinsic evidence to better inform gene predictions. The second is to use extrinsic evidence in tandem with predictions such that the influence of their respective biases in the consensus gene models is reduced. We benchmarked our new tool against three known pipelines, showing significant gains in gene, transcript, exon and intron sensitivity and specificity in the genome annotation of microbial eukaryotes

Whole genome duplication analysis of the invasive Lonicera maackii (Amur honeysuckle)

Invasive Lonicera maackii (L. maackii) is one of the highly successful and problematic bush honeysuckles found in the central and eastern of United States of America, which has been reported to pose a threat to native ecosystems by decreasing biodiversity. The mechanism by which L. maackii negatively impact environments is typically through either the direct effect of increased dominance or the indirect effect of territory modification. Numerous studies have documented the negative effects of L. maackii on native biota and the key traits such as seed dispersal, phenology, resistance to herbivory, rapid growth and environmental plasticity that contribute to invasion of L. maackii. In past decades, the studies mainly focused on negative effects and management of L. maackii invasion, and little was done to explore the genetic traits contributing to devastate the native ecosystem. Chloroplast-based genomic and chemical diversity in L. maackii has been reported. However, the whole genomic diversity in L. maackii has not been reported due to the availability of whole genome sequence of L. maackii. The advances in whole genome sequencing technologies and bioinformatic tools allow for studying the genomic diversity of L. maackii at the whole genome level. Genome duplication is a key evolutionary mechanism providing new genetic materials and new gene functions for plants, which play important roles in speciation and adaptation to biotic/abiotic stress. Given the fact that L. maackii is closely related to L. japonica, and whole genome duplication of Lonicera japonica (L. japonica) has been reported (Pu et al., 2020; Yu et al., 2022), we hypothesize that a whole genome duplication is present in L. maackii. In this study, we aim to investigate whether there is a genome duplication in L. maackii with the purpose of exploring the genomic diversity in L. maackii. We also conducted a comparison of genome duplication among the species in Lonicera genus. With the completion of whole genome assembly of L. maackii (Kesel et al., 2022), we conducted the gene prediction using Exonerate and gene duplications analysis using MCScanX in L. maackii. As a result, we predicted 32,642 genes and identified 5,668 genes, 24,911 genes, 703 genes, 902 genes, and 458 genes deriving from Singleton, Dispersed, Proximal, Tandem, and WGD modes, respectively. To our knowledge, this is the first genome duplication analysis that has been reported in L. maackii. Compared to L. japonica, a higher prevalence of Singleton and Dispersed modes of gene duplication was observed in L. maackii. The different genome duplication patterns between L. maackii and L. japonica may result from the difference of whole genome assembly format. The future directions should focus on improving the chromosome-scale genome assembly and whole genome annotation, promoting our understanding on the genome diversity and evolutionary traits in L. maackii and controlling the expansion of L. maackii

Genome and transcriptome analysis of the Mesoamerican common bean and the role of gene duplications in establishing tissue and temporal specialization of genes

Background: Legumes are the third largest family of angiosperms and the second most important crop class. Legume genomes have been shaped by extensive large-scale gene duplications, including an approximately 58 million year old whole genome duplication shared by most crop legumes. Results: We report the genome and the transcription atlas of coding and non-coding genes of a Mesoamerican genotype of common bean (Phaseolus vulgaris L., BAT93). Using a comprehensive phylogenomics analysis, we assessed the past and recent evolution of common bean, and traced the diversification of patterns of gene expression following duplication. We find that successive rounds of gene duplications in legumes have shaped tissue and developmental expression, leading to increased levels of specialization in larger gene families. We also find that many long non-coding RNAs are preferentially expressed in germ-line-related tissues (pods and seeds), suggesting that they play a significant role in fruit development. Our results also suggest that most bean-specific gene family expansions, including resistance gene clusters, predate the split of the Mesoamerican and Andean gene pools. Conclusions: The genome and transcriptome data herein generated for a Mesoamerican genotype represent a counterpart to the genomic resources already available for the Andean gene pool. Altogether, this information will allow the genetic dissection of the characters involved in the domestication and adaptation of the crop, and their further implementation in breeding strategies for this important crop.La lista completa de autores que integran el documento puede consultarse en el archivo.Facultad de Ciencias ExactasInstituto de Biotecnologia y Biologia Molecula